Spectral Decomposition By Schur for Medical Ultrasound Image Denoising

Al‐Asad, Jawad F.; Butt, Muhammad Omair; Khan, Adil H.

doi:10.1109/isaect47714.2019.9069688

Cited by 1 publication

(2 citation statements)

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“…In [19], Schur decomposition is proposed for eigenvalue decomposition, and initial vectors were selected to minimize the effect of speckle noise. Frequency domain analysis is incorporated with Schur decomposition in [2], which secures much better results due to the analysis in the frequency domain. The drawback of these methods is the complexity of the algorithm.…”

Section: Recent Workmentioning

confidence: 99%

“…The major disadvantage carried by ultrasound images is the inclusion of multiplicative noise, also known as speckle noise, during the process of image acquisition [2]. A high amount of speckle-noise is accumulated in ultrasound images due to a complex phenomenon of destructive and constructive interference of echoes from various neighboring tissue parts in the body.…”

Section: Introductionmentioning

confidence: 99%

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Frequency domain despeckling technique for medical ultrasound images

Al‐Asad

Mewada

Khan

et al. 2021

Journal of Electrical Engineering

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This work proposes a novel frequency domain despeckling technique pertaining to the enhancement of the quality of medical ultrasound images. The results of the proposed method have been validated in comparison to both the time-domain and the frequency-domain projections of the schur decomposition as well as with several other benchmark schemes such as frost, lee, probabilistic non-local means (PNLM) and total variation filtering (TVF). The proposed algorithm has shown significant improvements in edge detection and signal to noise ratio (SNR) levels when compared with the performance of the other techniques. Both real and simulated medical ultrasound images have been used to evaluate the numerical and visual effects of each algorithm used in this work.

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Section: Recent Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%